This SBIR Phase I project will prove the concept for a low-cost, point-of-care system for real-time diagnosis of candidemia (fungal infection of blood). Hospital-acquired infections occur in ~10% of the patients in critical care facilities in the US, and Candida species are currently the 4th leading cause of blood stream infection. They are associated with attributable mortality that approaches 40%, which is in part a reflection of insensitive diagnostics leading to relatively late therapy. Too often conventional diagnostics fail to identify fungal infection and a confirmed detection is made only post mortem. Existing fungal detection methods are slow. Culture is the gold-standard, but this often takes up to 72 hours. Other methods, such as PCR are being explored, but these methods are often time-intensive as well;often requiring more than 24h to complete. It has been shown (Kumar et al., 2006) that there is a 7% rise per hour, after the onset of septic shock, in the mortality rate from untreated sepsis in general. This proposal will explore a novel method which has the potential to detect Candida down to the level of a single microorganism in a human blood sample in minutes and to diagnose the species in ~2 hours. The objective of this Phase I effort is to build and test a proof-of-concept cell-sorting method, Fountain Flow" Sorting, for the detection of fungi in blood. A stream of blood containing an inexpensive fluorescent, fungal dye is illuminated with an LED, and fluorescent fungal cells are detected with a digital camera. After each detection, a fungal cell is sorted into a smaller volume, which can be then stained with more-expensive, RNA dyes for species identification, allowing the use of more-effective and/or cost-effective therapy targeted to a specific strain. Phase I research and development will focus on the detection and differentiation of Candida albicans and Candida glabrata, two of the most common strains of Candida. The difference in efficacy, toxicity, and expense of differing drug therapies between these two species is considerable. No other method has the capability to providing rapid, economical detection and fungal species discrimination at the level achievable with Fountain Flow" sorting combined with RNA fluorescent dyes. This research wil be performed by a team of scientists from SoftRay Inc. in collaboration with its University of Wyoming SBIR partner, a transfusion medicine consultant (Bonfils Blood Center, Denver) and a clinical microbiologist (Cleveland Clinic). PUBLIC HEALTH RELEVANCE: Septicemia is the tenth leading cause of death in the US and has the third highest mortality rate among infectious diseases, behind pneumonia and influenza, higher than HIV. Roughly 40% of the deaths caused by sepsis are due to fungal infections. This project proposes a system that will provide for lower-cost, more timely and more sensitive detection of fungal contamination, allowing for earlier antifungal treatment where speed and sensitivity of detection are critical.